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» A Parallel Algorithm for Gene Expressing Data Biclustering
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87
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BMCBI
2006
106views more  BMCBI 2006»
14 years 10 months ago
Methodological study of affine transformations of gene expression data with proposed robust non-parametric multi-dimensional nor
Background: Low-level processing and normalization of microarray data are most important steps in microarray analysis, which have profound impact on downstream analysis. Multiple ...
Henrik Bengtsson, Ola Hössjer
105
Voted
JBI
2004
171views Bioinformatics» more  JBI 2004»
14 years 11 months ago
Consensus Clustering and Functional Interpretation of Gene Expression Data
Microarray analysis using clustering algorithms can suffer from lack of inter-method consistency in assigning related gene-expression profiles to clusters. Obtaining a consensus s...
Paul Kellam, Stephen Swift, Allan Tucker, Veronica...
SDM
2008
SIAM
123views Data Mining» more  SDM 2008»
14 years 11 months ago
Constrained Co-clustering of Gene Expression Data
In many applications, the expert interpretation of coclustering is easier than for mono-dimensional clustering. Co-clustering aims at computing a bi-partition that is a collection...
Ruggero G. Pensa, Jean-François Boulicaut
ICTAI
2007
IEEE
15 years 4 months ago
Accurate Classification of SAGE Data Based on Frequent Patterns of Gene Expression
In this paper we present a method for classifying accurately SAGE (Serial Analysis of Gene Expression) data. The high dimensionality of the data, namely the large number of featur...
George Tzanis, Ioannis P. Vlahavas
BMCBI
2004
150views more  BMCBI 2004»
14 years 10 months ago
Rank Difference Analysis of Microarrays (RDAM), a novel approach to statistical analysis of microarray expression profiling data
Background: A key step in the analysis of microarray expression profiling data is the identification of genes that display statistically significant changes in expression signals ...
Dietmar E. Martin, Philippe Demougin, Michael N. H...